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|a Mastering OpenCV 4 :
|b a comprehensive guide to building computer vision and image processing applications with C++ /
|c Roy Shilkrot, David Millán Escrivá.
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|a Mastering Open Computer Vision four
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|a Third edition.
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|a Mastering OpenCV 4 : a comprehensive guide to building computer vision and image processing applications with C++ -- Contributors -- Table of Contents -- Preface -- Chapter 1: Cartoonifier and Skin Color Analysis on the RaspberryPi -- Chapter 2: Explore Structure from Motion with the SfM Module -- Chapter 3: Face Landmark and Pose with the Face Module -- Chapter 4: Number Plate Recognition with Deep Convolutional Networks -- Chapter 5: Face Detection and Recognition with the DNN Module -- Chapter 6: Introduction to Web Computer Vision with OpenCV.js -- Chapter 7: Android Camera Calibration and AR Using the ArUco Module -- Chapter 8: iOS Panoramas with the Stitching Module -- Chapter 9: Finding the Best OpenCV Algorithm for the Job -- Chapter 10: Avoiding Common Pitfalls in OpenCV -- Other Books You May Enjoy -- Index.
|
520 |
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|a Mastering OpenCV, now in its third edition, targets computer vision engineers taking their first steps toward mastering OpenCV. Keeping the mathematical formulations to a solid but bare minimum, the book delivers complete projects from ideation to running code, targeting current hot topics in computer vision such as face recognition, landmark detection and pose estimation, and number recognition with deep convolutional networks. You'll learn from experienced OpenCV experts how to implement computer vision products and projects both in academia and industry in a comfortable package. You'll get acquainted with API functionality and gain insights into design choices in a complete computer vision project. You'll also go beyond the basics of computer vision to implement solutions for complex image processing projects. By the end of the book, you will have created various working prototypes with the help of projects in the book and be well versed with the new features of OpenCV4.
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